Triple
T2814075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Capital Region (Canada) |
E54240
|
entity |
| Predicate | includesTypeOfArea |
P36978
|
FINISHED |
| Object | urban areas |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: urban areas | Statement: [National Capital Region (Canada), includesTypeOfArea, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTypeOfArea Context triple: [National Capital Region (Canada), includesTypeOfArea, urban areas]
-
A.
includesAreaType
chosen
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
-
B.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
includesAreasOff
Indicates that something encompasses or covers areas that are turned off, inactive, or excluded from normal operation.
-
D.
campusAreaType
Indicates the classification of a campus area according to its type or functional category.
-
E.
includedTerritoryType
Indicates that one territory type is contained within, or forms part of, another territory type.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ba34c819085a336498fc326b0 |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.